1. Field of the Invention
The disclosed embodiments of the present invention relate to a defect analysis method, and more particularly, to a systematic defect analysis method which is able to analyze defects with respect to given physical characteristics.
2. Description of the Prior Art
To fix yield problems in IC manufacturing, identifying root causes of systematic defects is critical. Physical failure analysis (PFA) is conducted on selected dies to understand defect mechanisms. Since PFA is a time-consuming and expensive process, the selection of dies should be carefully guided by systematic defect diagnosis. In recent studies, many dies have been discovered which have multiple defects; this issue therefore cannot be ignored in systematic defect diagnosis.
With suspected physical sites identified from several failing chips, many statistical analysis techniques have been proposed for systematic defect diagnosis, i.e. determining common root cause(s) of multiple defects among the failing chips. Statistical learning and layout-aware diagnosis have been proposed to estimate the failure rates of physical features. Statistical independence inference and causal inference have been used in systematic defect diagnosis to evaluate DFM rules. The chi-square test technique has been used to identify dominant open features, and the Z-test has been used to identify layers of systematic defects. Most of the abovementioned techniques do not analyze a trend of defect occurrences associated with a given physical feature.
In light of the above, there is an urgent need for a novel systematic defect analysis method which can improve the issues of the prior art.